Abstract
The digital transformation of higher education has increased the need to develop technological strategies and engineering designs aimed at supporting students' emotional well-being in virtual environments. The objective of this study was to develop an engineering design to support anxiety management in digital university environments. The study adopted a quantitative approach with a quasi-experimental design and involved 240 university students distributed into an experimental group and a control group. The platform integrated emotional monitoring, predictive analysis, and adaptive intervention mechanisms through machine learning algorithms. The results showed a significant reduction in anxiety, stress, and cognitive load in the experimental group, as well as high levels of predictive accuracy in the implemented models. It is concluded that adaptive artificial intelligence represents a viable alternative for strengthening more human-centered and preventive digital educational ecosystems.
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